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混合脑机接口及其研究进展 被引量:6

Research Development on Hybrid Brain-Computer Interface
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摘要 脑机接口(brain-computer interface,BCI)技术作为一项新兴且发展潜力巨大的技术,已成为国际研究热点;但面向实际应用,现有BCI技术仍面临许多有待解决的问题,如基于稳态视觉诱发(SSVEP)的BCI技术控制命令数有限,基于运动想象(motor imagery,MI)的BCI存在诱发生理信号空间分辨率低、训练时间长等问题;研究表明,混合脑机接口(hybrid brain-computer interface,HBCI)相比于传统单模态BCI系统,在系统准确率、稳定性方面均有所提升;文章对HBCI进行了介绍,从基于多脑电模式的混合脑机接口、基于多种刺激诱发的混合脑机接口、基于多模态信号的混合脑机接口这三个类别分别对HBCI的研究进展进行阐述,并对HBCI关键技术、需要解决的问题及应用方向进行了概述。 As a potential technology,brain-computer interface(BCI)has become an international research hotspot.However,for practical application,the existing BCI technology still faces many problems to be solved,such as the limited number of control commands of steady-state visual evoked potential(SSVEP)based BCI,the low spatial resolution of induced physiological signals and the long training time of motor imagination(MI)based BCI.Some studies have shown that the hybrid brain computer interface(HBCI)is more accurate and stable than the traditional BCI(single-mode brain computer interface).In this paper,the concept of HBCI is introduced.And the research progress of HBCI,including multi-EEG modes based HBCI,multi-simulation induction based HBCI and multi-modal signals based HBCI,is described.In addition,the key technology,the problems and the application of HBCI are summarized.
作者 雍颖琼 张宏江 程奇峰 孙光 阳佳 Yong Yingqiong;Zhang Hongjiang;Cheng Qifeng;Sun Guang;Yang Jia(China Academy of Launch Vehicle Technology,R&D Department,Beijing 100076,China)
出处 《计算机测量与控制》 2020年第9期9-13,28,共6页 Computer Measurement &Control
基金 国家重点研发计划(2017YFB1300305)。
关键词 混合脑机接口 SSVEP P300 多模 hybrid brain computer interface SSVEP P300 multi-modal
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  • 1李凌,尧德中,刘铁军,赵丽娜.刺激前后脑电α波相位重排现象研究[J].电子科技大学学报,2006,35(1):118-121. 被引量:3
  • 2Wolpaw JR, cFarland D J, Vaughan TM. Brain-Computer Interface Research at the Wadsworth Center. IEEE Transactions on Rehabilitation Engineering, 2000, 8 (2): 222-226.
  • 3Steven G.Mason, Gary E. Birch. A General Framework for Brain- Computer Interface Design. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2003, 11 ( 1 ) : 70 - 85.
  • 4Touradj Ebrahimi, Jean-Marc Vesin, Gary Garcia. Brain-computer Interface in Multimedia Communication. IEEE Signal Processing Magzine , 2003, 1:14-24.
  • 5Gary E. Birch, Steven G. Mason, Jaimie F. Borisoff. Current Trends in Brain-Computer Interface Research at the Neil Squire Foundation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2003, 11 (2): 123- 126.
  • 6Wolpaw JR, Birbaumer N, Heetderks WJ. Brain computer interface technology : a review of the first international meeting. IEEE Trans Rehab Eng , 2000 , 8 (2): 164- 173.
  • 7Sykacek P, Roberts S, Stokes M. Probabilistic Methods in BCI Research. IEEE Transactions on Rehabilitation Engineering, 2003,11(2): 192-195.
  • 8Donchin E, Spencer KM, Wij Esinghe R. The mental prosthesis:Assessing the speed of a P300-based brain-computer interface. IEEE Trans Rehab Eng, 2000, 8 (2) : 174- 179.
  • 9Matthew Middendorf, Grant McMinan, Gloria Calhoun. Brain-Computer Interfaces Based on the Steady-State Visual-Evoked Response. IEEE Transactions on Rehabilitation Engineering, 2000,8 (2) : 211-214.
  • 10Cheng M, Gao S. EEG-based cursor control system. Proc. Annu.Int. Conf. IEEE Engineering in Medicine and Biology Soc, 1999,669.

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